Monitoring leakage in aeronautical band of high split hfc

ABSTRACT

A method for monitoring leakage in an aeronautical band of a high split HFC by a detection and validation of OUDP bursts includes: providing an apparatus for use in a patrol vehicle, the apparatus including a leak signal receiver coupled to a processor; measuring a duration of detected bursts to provide a plurality of burst durations; collecting a histogram of the burst durations during a measuring session to provide a duration histogram; and determining a presence of a leak based on a comparison of the duration histogram with expected durations of OUDP bursts. Systems for monitoring leakage in an aeronautical band of a high split HFC by a detection and validation OUDP bursts, and other methods for monitoring leakage in an aeronautical band of a high split HFC by a detection and validation OUDP bursts are also described.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part (CIP) of U.S. patentapplication Ser. No. 17/088,775, MONITORING LEAKAGE IN AERONAUTICAL BANDOF HIGH SPLIT HFC, filed Nov. 4, 2020, now allowed, and claims priorityto and the benefit of U.S. provisional patent application Ser. No.62/930,030, LEAKAGE DETECTION WITHIN THE UPSTREAM BANDWIDTH OF AN HFCNETWORK, filed Nov. 4, 2019, U.S. provisional patent application Ser.No. 62/969,238, METHOD OF MONITORING LEAKAGE AT AERONAUTICAL BAND OFHIGH-SPLIT HFC NETWORK, filed Feb. 3, 2020, U.S. provisional patentapplication Ser. No. 63/006,355, MONITORING LEAKAGE IN AERONAUTICAL BANDOF HIGH SPLIT HFC, filed Apr. 7, 2020, all of which applications areincorporated herein by reference in their entirety.

FIELD OF THE APPLICATION

The application relates to signal leakage detection in a HybridFiber-Coaxial (HFC) network, particularly to upstream leak detection.

BACKGROUND

The task of detecting leakage from the coaxial part of an HFC network isvery important, such as, for preventing interference at the aeronauticaland LTE bands and for isolation of ingress in the return path of the HFCnetwork. In legacy DOCSIS 3.0 HFC networks, the aeronautical band(108-137 MHz) is overlapped with the downstream bandwidth. For leakagedetection, downstream signals such as analog video carriers or pilotsare injected into a guard bandwidth between downstream QAM channels, orthere can be cross correlation detection of the QAM downstream channel(See for example, QAM Snare product,<https://www.arcomdigital.com/qam-snare/> available from Arcom ofSyracuse, N.Y.), or for DOCSIS 3.1 networks, detection of pilotharmonics of the OFDM signal (See for example, U.S. Pat. No. 9,832,089,also assigned to Arcom Digital LLC, and incorporated herein by referencein its entirety for all purposes) has also been used.

SUMMARY

A method for monitoring leakage in an aeronautical band of a high splitHFC by a detection and validation of OUDP bursts includes: providing anapparatus for use in a patrol vehicle, the apparatus including a leaksignal receiver coupled to a processor; measuring a duration of detectedbursts to provide a plurality of burst durations; collecting a histogramof the burst durations during a measuring session to provide a durationhistogram; and determining a presence of a leak based on a comparison ofthe duration histogram with expected durations of OUDP bursts.

After the step of providing and before the step of determining, themethod can further include the steps of: sending GPS coordinates of alocation of the patrol vehicle to a leakage data server; and receiving aplurality of expected durations of OUDP bursts for a current location ofthe patrol vehicle.

If the comparison of the duration histogram with the expected durationsof OUDP bursts exceeds a threshold, the method can include sending areport to the leakage data server including a time stamp, a GPScoordinate, and a leak level.

A display can be operatively coupled to the processor and after the stepof comparing, a step of determining the presence of the leak can includeshowing an indication of a detected leak on a map in a vicinity of thecurrent location of the patrol vehicle.

An upstream leak detection system for monitoring leakage in anaeronautical band of a high split HFC by a detection and validation OUDPbursts includes a leak detection apparatus configured for use in amobile patrol vehicle. The leak detection apparatus includes: aprocessor, a leakage receiver including a burst leak signal detector tomeasure a duration of detected bursts, the leakage receiver operativelycoupled to the processor. A leakage data server includes a database withcable modems (CMs) physical and IP addresses and a core to stimulate anupstream traffic from a plurality of CM in a current vicinity of themobile patrol vehicle.

A method for monitoring leakage in an aeronautical band of a high splitHFC by a detection and validation OUDP bursts includes: providing anapparatus for use in a patrol vehicle, the apparatus including a leaksignal receiver coupled to a processor; auto-correlating cyclic prefixesof OFDMA symbols within OUDP bursts by one or more autocorrelationfunctions to provide a plurality of coherent responses; and determininga presence of a leak based on an accumulation of the plurality ofcoherent responses.

After the step of providing and before the step of determining, themethod can further include the steps of: sending GPS coordinates of alocation of the patrol vehicle to a leakage data server; and receiving aplurality of expected coherent responses for a current location of thepatrol vehicle.

If the step of determining the presence of a leak based on theaccumulation of the plurality of coherent responses exceeds a threshold,the method can include sending a report to the leakage data serverincluding a time stamp, a GPS coordinate, and a leak level.

A display can be operatively coupled to the processor and the step ofdetermining the presence of the leak, can include showing an indicationof a detected leak on a map in a vicinity of the current location of thepatrol vehicle.

An upstream leak detection system for monitoring leakage in anaeronautical band of a high split HFC by a detection and validation OUDPbursts includes a leak detection apparatus configured for use in amobile patrol vehicle. The leak detection apparatus includes aprocessor, a leakage receiver including a burst leak signal detectorincluding a process to auto-correlate cyclic prefixes of OFDMA symbolswithin OUDP bursts by one or more autocorrelation functions to provide aplurality of coherent responses, the leakage receiver operativelycoupled to the processor. A leakage data server includes a database withcable modems (CMs) physical and IP addresses and a core to stimulate anupstream traffic from a plurality of CM in a current vicinity of themobile patrol vehicle.

The foregoing and other aspects, features, and advantages of theapplication will become more apparent from the following description andfrom the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The features of the application can be better understood with referenceto the drawings described below, and the claims. The drawings are notnecessarily to scale, emphasis instead generally being placed uponillustrating the principles described herein. In the drawings, likenumerals are used to indicate like parts throughout the various views.

FIG. 1 is a block diagram of the system for detection leakage inupstream bandwidth of HFC network;

FIG. 2 is a time domain diagram of ATDMA burst signal;

FIG. 3 is time domain diagram of OFDMA burst signal;

FIG. 4 illustrates typical histograms of distribution durations forimpulse noise and upstream bursts;

FIG. 5 is block diagram of upstream leak detector;

FIG. 6 is time diagram illustrated detection envelope, time stamp andduration of impulses;

FIG. 7 is block diagram of auto-correlation detector preamble ATDMAbursts;

FIG. 8 is time diagram illustrated detection preamble of ATDMA bursts;

FIG. 9 is block diagram of auto-correlation detector cyclic prefix OFDMAbursts;

FIG. 10 is time diagram illustrated detection cyclic prefix of OFDMAbursts;

FIG. 11 is a flow diagram outlining algorithm of controller formeasuring and validation burst leak signal and ambient impulse noise;and

FIG. 12 illustrates two exemplary pages of a leak detector display forthe indication of results of detection leak and impulse noise and forthe identification of the MAC address of the CM which generated thedetected leak signal.

FIG. 13 is a drawing showing a diagram of an exemplary system formonitoring leakage in aeronautical band of high split HFC;

FIG. 14 is a drawing illustrating the concept permanent generation by CMOUDP bursts for monitoring leakage.

FIG. 15 is a drawing which shows an example of an OUDP burst signal intime-frequency domain for a pilot pattern;

FIG. 16 is a drawing which illustrates binary phase shift keying (BPSK)modulation of OUDP pilots according to DOCSIS 3.1 specs;

FIG. 17 is a drawing showing a block diagram of an OUDP burst detectorwith an adaptive matched filter and on-line receiving of coefficients ofa matched filter from the leak data server;

FIG. 18 is a is flow chart showing an exemplary operation of an OUDPleak detector according to the Application;

FIG. 19 is a drawing showing a graph which illustrates an exemplaryactual correlation process at the output of OUDP matched filter for apilot pattern;

FIG. 20 is a graph which illustrates the concept of a process algorithmfor the selection of dominant peaks;

FIG. 21A is a drawing showing a flow chart of an exemplary leak dataserver operation after an operator presses the “Map” button at a fieldunit;

FIG. 21B is a drawing showing exemplary display screens of an exemplaryOUDP detector with “Map” mode with detection MAC address;

FIG. 22 is a drawing showing a block diagram of an exemplary embodimentof system for monitoring leakage at aeronautical band of high split HFCnetwork according to the present application, part 3;

FIG. 23 is a drawing showing the structure of an exemplary pilot signalgenerated by a CM;

FIG. 24 is a drawing showing an exemplary combination of pilots fromdifferent CMs;

FIG. 25 is a drawing showing an exemplary pilot signal placed into anexclusion bandwidth of an upstream OFDMA spectrum;

FIG. 26 is a drawing showing a block diagram of an exemplary leakagedetector suitable to perform new CW methods of the Application;

FIG. 27 is a drawing showing a graph of time versus frequency forexemplary OFDMA bursts at F1 and F2; and

FIG. 28 is a drawing showing exemplary CW test signal in the exclusionbandwidth adjacent to active OFDMA subcarriers.

DETAILED DESCRIPTION Definitions

Ping—When a modem, such as a cable modem (CM) is “pinged” by a commandsent to the modem, the modem generates a reply, such as a reply copyinga payload message sent to the modem as part of the ping. Typically, amodem returns a packet sent to it, however we use the term moregenerally hereinbelow, where a ping includes any command sent to amodem, which causes some data to be returned by the modem. The returneddata can be, for example, a packet, a series of packets (such as causedby a series of pings), or any other suitable data payload. That is, theterm ping, as used hereinbelow includes any suitable commandintentionally sent to a modem, which causes the modem to return at leastone data packet. The phrase, “command sent to a CM which causes at leastone return data packet”, can be used interchangeably for the word “ping”in the Application. Ping also includes generation by a CM of anysuitable signal into the upstream cable path, including a probing OFDMAsignal or an OUDP burst.

The Application is divided into four parts. Part 1 describes leakagedetection within the upstream bandwidth of an HFC network using QAM andOFDMA burst techniques. Part 2 describes monitoring leakage inaeronautical band of high split HFC using OUDP leakage detectiontechniques. Part 3 describes methods of monitoring leakage ataeronautical band of high-split HFC network using CW signals. Part 4describes a CW-TDMA mode.

Part 1—QAM and OFDMA Burst

As described hereinabove, the task of detecting leakage from the coaxialpart of a HFC network is very important, such as, for preventinginterference at the aeronautical and LTE bands and for isolation ofingress in the return path of the HFC network. In legacy DOCSIS 3.0 HFCnetworks, the aeronautical band (108-137 MHz) is overlapped with thedownstream bandwidth. For leakage detection, downstream signals such asanalog video carriers or pilots are injected into a guard bandwidthbetween downstream QAM channels, or there can be cross correlationdetection of the QAM downstream channel (See for example, QAM Snareproduct, <https://www.arcomdigital.com/qam-snare/> available from Arcomof Syracuse, N.Y.), or for DOCSIS 3.1 networks, detection of pilotharmonics of the OFDM signal (See for example, U.S. Pat. No. 9,832,089,also assigned to Arcom Digital LLC, and incorporated herein by referencein its entirety for all purposes) has also been used.

Leakage detection at the aeronautical band can also be used for thelocation of possible “holes” where ingress is injected into the returnbandwidth of the HFC network. This method is based on an assumption thatthe frequency response of coaxial cable at point of generation leakageat the aeronautical band is similar to the frequency response of thepoint injection Ingress at an upstream bandwidth of 5-42 MHz.

The problems of detecting leakage at modern HFC DOCSIS 3.1 and nextgeneration of DOCSIS 4.0 (Full Duplex) networks are increased due to thefollowing factors.

The first important factor is that modern DOCSIS 3.1 and 4.0 networksmigrate to high split systems with return bandwidths of up to 204 MHz,and up to 684 MHz in the case of full duplex (FDX). In this scenario theaeronautical band 108-137 MHz will be overlapped with upstream bandwidthwhere a leak signal can be created by upstream signals from a cablemodem (CM).

Until the new system and method of this Application, leakage detectionat upstream bandwidth was simply not carried out and there are few knownmethods and apparatus for such detection.

A first problem in detection of upstream leakage signal is the fact thatthis is a spread spectrum ATDMA SC-QAM or OFDMA burst signal. Detectionof these signals is a much more difficult task compared with detectionof a downstream analog video carrier or CW pilots, because upstreambursts look like noise signals, and upstream traffic from CMs is a veryrandom process. For example, while patrolling for leakage, some CMscould be in a stand-by mode and not generate any upstream bursts. Thenext problem of detection burst leak signal is the presence at upstreambandwidth of ambient impulse noise. This impulse noise can have the samestructure as the burst signal from CMs and as a result, impulse noiseprovides an interfering impact on a leak detector by creating false leakalarms.

The second relevant aspect of detection of leakage at the upstreambandwidth is location of possible zones where ingress enters the networkat the upstream bandwidth. First, detection of leakage at the sameupstream bandwidth will definitely be a more accurate indicator for thelocation of potential “holes” of injection Ingress into coaxial cable ascompared to using downstream bandwidth. Second, it is well known thatthe majority of “holes” where ingress is injected into the network arelocated at the drop portion of the network, because the quality(shielding efficiency) of drop coax cable is not as good as the qualityof trunk cable. Additionally, the level of upstream signals at the dropnetwork is from +35 dBmV to +55 dBmV, which is much higher than thelevel of the downstream signals (0 . . . +10 dBmV).

Such a big difference of signal levels allows for the reasonableassumption that the location of ingress “holes” at drop lines viadetection of upstream leaks, will be more effective, compared todetection of leaks from low level downstream signals because theupstream signal levels are inherently larger.

As was noted above, status quo, there typically is no leakage detectionperformed at the upstream bandwidth and there are few special methodsand apparatus for this sort of leak detection. Of course, for detectionof return leakage, modern spectrum analyzers (SA) with FFT overlappingmode and “waterfall” indication could be used. However, a SA is a veryexpensive tool for mass field application. Because human analysis ofmeasuring results is typically required, this method by SA is not verygood for an automatic leak patrolling mode. Also, this SA method doesnot provide a good validation of upstream bursts in presence of strongambient impulse noise, which will mask the haystack spectrums of theATDMA SC-QAM bursts and the minislot spectrums of OFDMA bursts.

One known method of identification of upstream ATDMA bursts wasdescribed in U.S. Pat. No. 8,427,974. The identification processincludes triggering on a rising edge of receiving burst signal and thenidentification of burst type by using a correlation processor for thepreamble waveform. This method assumes that preambles of waveforms areknown a priori for all Short Grand, Long Grand and Unsolicited Grandbursts, or that the preamble can be extracted by receiving the upstreamchannel descriptor (UCD) from the CMTS. The correlation method ofpreamble waveform is an effective method of identification andvalidation upstream ATDMA burst, but in the scenario of a vehiclepatrolling for leakage, receiving UCD from different CMTSs andgeneration of ATDMA preamble waveforms is not a trivial task, becausethe UCD could change from hub to hub and from node to node, especiallyin a distributed HFC architecture (with remote PHY and MAC-PHY). So,this method should be used for a permanent on-line process of receivingUCDs, creating preamble waveforms and re-programming correlationprocessor. Such an approach will definitely cause an increasingcomplexity and cost of a leak detection system and would also havelimitations in areas with poor communication.

Thus, there is a need for a low cost automatic and valid detection ofleakage in the upstream bandwidth, especially for modern HFC. TheApplication describes new system and method solutions which provide forlow cost automatic leakage detection in the upstream bandwidth of theHFC network.

The Application also describes a method to stimulate upstream trafficfrom groups of CMs located at the leakage patrolling zone by sendingpings to IP addresses of corresponding CMs from a database containing CMIP addresses and GPS coordinates of the homes. The Application alsodescribes a method of forcing CMs to transmit burst signals at someselected upstream channel for purposes of upstream leakage detection.

The Application also describes a method of validation upstream leakbursts by analyzing the duration and time stamps of detected impulses,and by auto-correlation detection for the presence of the preamble inATDMA bursts and/or for cyclic prefix in OFDMA bursts.

The Application also describes a method of identification of the MACaddress of the CM which generated the detected upstream leak signal.

The Application also describes a method of detection of potentialingress events at the return path of HFC by analysis of leak signals andambient impulse noise.

The Application also describes a low-cost apparatus for the automaticdetection and validation leakage at upstream bandwidth of an HFCnetwork, including a field meter with a GPS receiver and a wirelessmodem, a remote leakage server and a software core for stimulation ofupstream traffic from CMs.

An exemplary system for detection leakage at upstream bandwidth of HFCnetwork according to the Application as illustrated in the schematicblock diagram of FIG. 1 is now described in detail. The exemplary systemof FIG. 1 includes a field leakage detector 114 installed on anysuitable vehicle, such as truck 101, and leakage data server 105. Fieldleakage detector 114 includes burst leak detector 102, GPS receiver 103and wireless modem 104. Leakage data server 105 includes database 115with the physical and IP addresses of the CMs and core for ping IPaddresses of CMs in coaxial network 106.

The exemplary system of FIG. 1 works as follows: Leakage detector 114sends each second report to leakage data server 105 with results ofdetection and the current GPS coordinates of truck 101. Leakage dataserver 105 selects in database 115, CMs 107, 108 and 109, which arelocated in the zone of truck 101, and send pings to IP addresses of CMs107, 108, 109. The server 105 generates sequential pings to provide acontinuous upstream traffic from CMs 107, 108 and 109. When the truck101 moves to other locations, the server 105 will select other groups ofCMs at nearest proximity from truck 101 for pings based on the GPSdetermined location of truck 101. This process can continueuninterrupted during a leakage patrol.

In the case of a shielding fault 112 (which creates a leak in network106) the upstream burst signal 113 from CM 107 will generate a leaksignal 110. This leak signal 110 is received by burst leak detector 102simultaneously with interfering ambient impulse noise 116 from differentunrelated industrial sources 117. Leak detector 102 measures parametersof each impulse and provides a validation of an actual burst leaksignals and prepares report to server 105 with leak and impulse noisedata.

For validation of actual upstream bursts and differentiating actualupstream bursts from ambient impulse noise at detector 102, a processalgorithm of the new method includes three stages: 1) analysis of theduration of the detected impulses; 2) detection of a preamble of ATDMAbursts and/or cyclic prefix in OFDMA burst; and 3) analysis of timestamps of the detected impulses.

Note that the Application uses an auto-correlation method for thedetection preamble of ATDMA burst and cyclic prefix of OFDMA burstswhich, different from the methods of the '974 patent, does not require apriori information about the preamble waveform and/or permanent on-linereceiving UCD from CMTS, or from leakage data server 105. This providesa new method which is described hereinbelow in more detail and offersmuch more flexibility and simplicity of detection method.

For a better understanding validation algorithm of burst leak signal thetime diagrams of ATDMA and OFDMA bursts are shown in FIG. 2 and FIG. 3accordingly.

ATDMA burst 201 of FIG. 2 includes preamble 203, packet data 204, FECParity 205 and Guard time interval 206. The duration of burst 201 Ti isequals to integer number K of minislots: Ti=K×T minislots, where K=2, 3. . . 255.

The next burst 202 starts from the moment of time t=M minislots relativeto burst 201. The rising edges of all of the ATDMA bursts are located inminislots on a time grid. This fact allows, as described in more detailhereinbelow, for the time stamp of a rising edge to be used forvalidation ATDMA bursts. The duration of one minislot is an integervalue of tick 6.25 μs. The typical number of ticks in a minislot forSC-QAM 64 is 1 or 2. The maximal number of minislots in one burst is255. Thus, the expected range of durations ATDMA bursts approximatelycan be estimated as follows:

Ti(min/max)=(2×T minislot×1 ticks)/(2×T minislots×2 tick×255)=from 12.5μs to 6,375 μs.

However, the maximal duration of bursts is typically less than 255minislots and limited in CMTS and/or by the IUC “Max burst” parameter inUCD. From a practical observation, the typical maximal duration of ATDMAbursts is no more than about 3 to 4 ms. It should be note, that actualactive duration of ATDMA burst is less on guard time 206 (FIG. 2). Thetypical guard time is approximately 0.5 to 1 μs, so, this is a verysmall part of the bursts, but the guard time should still be taken intoconsideration when performing a validation of the duration of the ATDMAbursts.

FIG. 3 shows a time domain diagram of an OFDMA burst signal. Theduration of OFDMA bursts 301 and 302 is defined by integer number ofactive symbols in frame. The duration of active OFDM symbol 303 Tsymbolis 20 μs for a 4 k FFT mode or 40 μs for an 8 k FFT mode plus durationof cyclic prefix 305 (0.9375 . . . 6.25 μs). The cyclic prefix 305 ispart 306 of OFDMA symbol 304, so, the waveform of cyclic prefix is thesame as at the end of OFDMA symbol and this property can be used for thevalidation of OFDMA bursts. The number of symbols contained in one frameis typically from 6 to 36. Thus, the range of duration or the OFDMAbursts is approximately from 125 μs to 1.665 ms. Note that the timeinterval between OFDMA bursts is also an integer number of M activesymbols, so, the time stamps of rising edge can be used for validationof the OFDMA bursts.

As was noted hereinabove, detection and validation of upstream leakbursts will be impacted by ambient impulse noise. The classical sourceof ambient impulse noise is power line arcing (e.g. source 117 in FIG.1). Cablelabs document CM-GL-PNMP-V02-110623 DOCSIS® Best Practices andGuidelines, Jun. 23, 2011 describes test results of investigationimpulse noise in many nodes. Based on these tests results Cablelabs cameto the following conclusion: “Impulses are short in duration, typicallyless than 20 microseconds (μs), and can fully cover the upstreamspectrum . . . From a duration perspective, it can be observed that mostimpulses have a duration that lasts less than 10 microseconds”.

The typical histogram of a number of impulses vs durations for ambientindustrial impulse noise is shown in FIG. 4, histogram 401. But itshould be noted, that histogram 401 is relevant for impulse noise withina full upstream bandwidth, while power line arcing can generate seriesof short pulses, which after passing through a band pass filter of anupstream receiver will intertwine and look like one to a few pulses witha duration similar to the duration of upstream bursts. Therefore, wherethe duration of the noise impulses falls within the range of duration ofupstream bursts, it would be not be correct to simply exclude thesecases, because they might be actual upstream bursts.

FIG. 4 shows a typical histogram 402 for upstream bursts. The level ofthe bars (number of bursts within different intervals of durations) istypically very random and depends from upstream traffic from the CM andthe settings (UCD) at CMTS. The short duration bursts 403 in histogram402 are ATDMA Request bursts. This type of burst is not good for leakdetection because its duration is within range of durations impulsenoise (histogram 401). Most preferable for leak detection in case ofATDMA are Long Grand (more that 128 bytes) bursts which are used forping response. The duration of these bursts is more than 20 μs whichallows one to exclude the majority of noise impulses from an analysisfor validation leak signal.

FIG. 5 is a block diagram showing an upstream leakage detector accordingto the Application.

This block diagram is common as for detection ATDMA and OFDMA bursts.Note, according to DOCSIS 3.1 specs ATDMA SC-QAM, an upstream signal canbe used only up to 85 MHz. At higher frequency bands an OFDMA signalshould be used. This means that at the aeronautical band of 108-137 MHzOFDMA burst leak detection should be used.

The detector of FIG. 5 includes: leak antenna 501, band pass filter(BPF) 502 for rejection out of Rx bandwidth interfering signals, lownoise amplifier (LNA) 503, low pass filter (LPF) 504, analog-to digitalconverter (ADC) 505, FPGA 506, CPU 513 with display 514, GPS receiver515 with antenna 516 and wireless modem 517 with antenna 518.

FPGA 506 is for the detection of burst leak signals. Digital samplesfrom ADC 505 comes to the input of I/Q down-converter 507 which is tunedon a central frequency of an ATDMA channel with a bandwidth 6.4 or 3.2MHz. In the case of detection of OFDMA bursts, the central frequency ofthe down-converter 507 should be tuned to a central frequency of an OFDMspectrum between adjacent OFDMA minislots. I/Q samples fromdown-converter 507 come to the input of envelop detector 508.

FIG. 6 shows an exemplary impulse signal 601 at the input of ADC 505 andthe signal 605 at the output of the envelop detector 508. The inputsignal 601 includes upstream burst 604 and noise impulses 602 and 603.The output signal 605 of envelope detector 508 includes envelope 608 ofburst 604 and envelopes 606, 607 of noise impulses 602 and 603. Thesignal 605 from output of envelope detector 508 comes to input ofcomparator 510 which detects the rising and falling edges of theenvelope signals. The threshold of the detection is shown as dashed line609. Plot 610 shows the signal at the output of comparator 510. Squarepulses 611 and 612 correspond to noise impulses 606 and 607 and pulse613 correspond to the burst signal 608.

Now, referring to both FIG. 5 and FIG. 6 together, signals fromcomparator 510 come to the inputs of impulse level meter 511 and toinput of controller 513. Impulse level meter 511 calculates the RMSlevel of the top of the envelope signals 605 from output of the envelopedetector 508. Data with impulses levels (Li) from meter 511 come tocontroller 512. Controller 512 measures time stamps 615 (ti−time ofrising edge) and duration 614 (Ti−time interval between rising andfalling edges) of each pulse at the output of comparator 510. As aresult, each detected impulse is associated in controller 512 with thefollowing data: time stamp ti, duration Ti and level Li. Note that timestamp ti is measured from the start time (zero time point) of ameasuring session at controller 512. A measuring session at controller512 is defined as the time interval during which controller 512 collectsdata. At the end of a measuring session, controller 512 sends data toCPU 513 and then starts a new measuring session. In the case of apatrolling leak detection truck, the reasonable duration of measuringsession is about one second.

Referring again back to block diagram in FIG. 5, the I/Q samples fromdown-converter 507 also comes to inputs of auto-correlation detector509. Auto-correlation detector 509 provides validation of ATDMA burstsby the detection of a presence of a preamble at the detected impulse ora validation of the OFDMA bursts by detection of the presence of an OFDMcyclic prefix. Controller 512 provides control and analysis data fromauto-correlation detector 509.

FIG. 7 is a block diagram showing an auto-correlation detector for ATDMApreambles.

FIG. 8 is a time diagram for the detection of preambles by theauto-correlation detector of FIG. 7. The idea of detection preamble isbased on an assumption that more than two bursts with the same preamblewill be detected during measuring sessions. In other words, event ofdetection preamble at current ATDMA burst means that early during thecurrent or the previous measuring session at least one burst with thesame preamble was detected. The advantage of this auto-correlationmethod is that information about the waveform of the preamble is notrequired at all. Note that the efficiency (peak to noise ratio) of theauto-correlation detector is no worse than the efficiency of optimalmatching filter in a case where the signal-to-noise ratio>0 (the exactscenario of detection of impulses at comparator 511).

The auto-correlation detector of FIG. 7 works as follows. The I/Qsamples come both to the input of correlation processor 704 and theinput of RAM 703. Write command 701 (803 in FIG. 8) to RAM 703 comesfrom controller 512 synchronous with the rising edge 802 of eachdetected impulse 801. As an example, FIG. 7 and FIG. 8 show that RAM 703stores I/Q samples corresponding a duration of one minislot 804. In thecase of SC-QAM 64 at Short Grand and Long Grand bursts, typically oneminislot (32 symbols or 64 QPSK bits) is used for the preamble. Parallelwith recording data into RAM 703 correlation processor 704 starts(command 805) calculation of the correlation functions 806 between inputI/Q samples and I/Q samples stored at RAM 705. Note that, at thebeginning of measuring session, RAM 705 stores samples from the previousmeasuring session.

After the detection of the falling edge 808 of an impulse 801,controller 512 measures the pulse duration Ti, and if the duration Ti iswithin an expected interval for a burst leak signal, then controller 512sends command 705 (810 in FIG. 8) to read the correlation data andcommand 809 to re-write I/Q samples from RAM 703 to RAM 705. Correlationdata 806 (a set of correlation functions between preamble of currentburst 801 and N previous bursts with valid duration) comes to controller512 for analysis. If a peak 807 is detected at one of the correlationfunctions 806, then the current detected pulse is identified incontroller 512 as a valid ATDMA burst.

The number N of stored minislots with I/Q samples in RAM 705 should belimited depending on the productivity of the correlation processor 704to provide a calculation of all of the correlation functions 806 untilthe falling edge 809 of burst 801. The minimal number is N=1. Detectionof a preamble event occurs when two pulses are detected in a row withvalid duration, and both pulses have the same preamble. Detection of apreamble event during a one second measuring session while pinging CMsis likely, especially where the Shot Grand and Long Grand bursts bothhave the same preamble (a common scenario). However, to increase theprobability of detection different preambles for a majority of validbursts, it makes sense to select a bigger value of N, for example N=8 .. . 32.

FIG. 9 is a block diagram of an OFDMA cyclic prefix auto-correlationdetector. FIG. 10 is a time diagram showing an exemplary detection of acyclic prefix.

The process of calculation of the auto-correlation process function iscontrolled by commands Start/Stop 905 (1004, 1005 in FIG. 10) fromcontroller 512. The Start/Stop commands are triggered by the rising 1002and falling 1003 edges of detected impulse 1001 accordingly. I/Q samples901 come to the input of the multiplier 902 and to the input of the timedelay line 903. The time delay in line 903 is 20 μs in a case of the 2 kFFT mode or 40 μs in a case of the 4 k FFT mode. If the FFT mode isprior un-known or can be changed from node to node, thenauto-correlation processor 509 should include two working channels inparallel for the 2K and 4K FFT modes. If a detected pulse is OFDMAbursts, then I/Q samples at the input of multiplier 902 will be coherent(have the same waveform) during the cyclic prefix, so, at the output ofmultiplier at the moment of an arriving cyclic prefix there will beformed a square pulse with a positive amplitude and a duration of cyclicprefix. In other moments of time in the inputs of multiplier 902 therewill be un-correlated samples from the OFDM symbol, and as a result atthe output of multiplier there will be a bi-polar noise signal. Thesignal from multiplier 902 comes to the input of Integrator 904 when theintegration time is equal to a duration of the cyclic prefix. If theduration of the cyclic prefix is prior unknown, then a multi channel (11channels) integrator should be used for all possible duration of cyclicprefix at OFDMA signal:

Upstream Cyclic Prefix 0.9375 μs  (96 * T_(su))  1.25 μs (128 * T_(su))1.5625 μs (160 * T_(su))  1.875 μs (192 * T_(su)) 2.1875 μs (224 *T_(su))   2.5 μs (256 * T_(su)) 2.8125 μs (288 * T_(su))  3.125 μs(320 * T_(su))  3.75 μs (384 * T_(su))   5.0 μs (512 * Tsu)  6.25 μs(640 * Tsu)

In the case of a detection of an actual OFDMA burst, the signal at theoutput of integrator 904 will include a series of peaks 1006 with aperiod of an ODFMA symbol. In the case of impulse noise, the peaks 1006will be absent. Thus, analysis of the auto-correlation process functionfor the presence of peaks 1006 allows for an effective validation ofOFDMA bursts in controller 512. Note that peaks 1006 could beadditionally accumulated in controller 512, so, the last peak will havea maximal of peak level ratio to noise which allows for a more robustvalidation.

Referring back to the block diagram of FIG. 5, controller 512 afterreceiving data from auto-correlation detector 509, assigns detectedpulses as either “Bursts leak” (a valid ATDMA or OFDMA) or “Impulsenoise”. Then, controller 512 splits all detected pulses into two files:a “Burst leak” file and an “Impulse noise” file, and at the end of themeasuring session send those files to CPU 513. The file “Burst leak”includes the following data: time stamp ti, duration Ti and level Li foreach burst. The file “Impulse noise” includes just the level Li of eachimpulse.

FIG. 11 is a flow chart of an exemplary algorithm which shows moredetail of the operation controller 513. After starting a new measuringsession at step 1101, the controller detects a new impulse at step 1102,and then at step 1103 measures time stamps ti, the duration of Ti andthe level Li of the detected impulse. Then at the next step 1104,controller 512 provides a verification duration of the detected impulse.If the duration is <20 μs, then the pulse is identified as an Impulsenoise and is recorded to the corresponding file (step 1108). If theduration of the signal at the output of integrator 904 is >=20 μs, thenthe at next step 1105, the controller provides a verification if theduration of the detected impulse is matched with the expected durationsATDMA or OFDMA bursts.

The interval “Delta” of the verification step 1105 is selected to coveraccuracy of measuring burst duration, inaccuracy of generation bursts inCM. The interval “Delta” of the verification step 1105 is selected tocompensate for the inaccuracy of the burst measurement and anyinaccuracy in the generation of bursts. For ATDMA bursts, the interval“Delta” should also include the expected Guard time of ATDMA bursts. Thetypical value of Delta for ATDMA bursts is in range from about 1 to 3μs.

If the verification at step 1105 is not passed, then the impulse isadded at step 1108 into file “Impulse noise”. If the verification atstep 1105 is okay, then the controller 512 reads correlation data fromdetector 509 and provides analysis correlation data at step 1106 on thepresence of an ATDMA preamble or of an OFDMA cyclic prefix.

If the verification at step 1106 is okay, then the detected pulse isadded to file “Burst leak” (step 1107), if not, then the impulse isadded to the file “Impulse noise” (step 1108). When the detectionsession is over (step 1109), controller 512 sends the files “Burst leak”and “Impulse noise” to the CPU 513 (step 1110) and then starts newmeasuring session (back to step 1101).

Again, referring back to the block diagram of FIG. 5, after receivingfile “Burst leak” CPU 513 provides an extra validation of the detectedbursts by checking for the condition where the time stamps ti arematched with minislot time grid (207 in FIG. 2) of ATDMA bursts or withsymbols time grid of OFDMA bursts (307 in FIG. 3). The algorithm ofverification matching with the time grid calculates the offset betweentI (time stamp of first detected burst) and time grid when maximalnumber of bursts will have matched time stamps+/−some delta (1 . . . 2μs). After calculation of an optimal offset, CPU 513 excludes from thefile “Burst leak” pulses with un-matched time stamps. Thus, the file“Burst leak” will include only bursts which satisfy three validitycriteria: 1) duration, 2) presence ATDMA preamble or OFDMA cyclic prefixand 3) matching time stamps with minislot or symbols time grid. It'svery robust criteria which excludes any false alarms of leak detection.

At next step, CPU 513 calculates a maximal (Max) level of bursts in thefile “Burst leak”, and this value then used as estimation of the returnleakage level during the measuring session. Also, CPU 513 calculates anaverage (AVG) level of noise impulses in the file “Impulse noise” andthen, this AVG value is used as estimate of the impulse noise levelduring measured session. Using the Max level for burst leak and the AVGlevel for impulse noise allows for a more accurate estimate of aninterfering event: “worst case” criteria for leakage and “reasonable”criteria for impulse noise.

Then, CPU 513 prepares the following data for indication on the display514: Leak level, number of detected bursts, Impulse noise level andnumber of detected noise impulses. Note that, the number of detectedbursts provides useful information for extra leak validation. The numberof detected noise impulses is also an informative parameter forgenerating impulse noise alarms. Parallel with the indication data shownon the display, CPU 513 combines measuring data with GPS time stamp andcoordinates and sends a report for server 105 via wireless modem 517.This process can be repeated for each measuring session.

FIG. 12 shows an exemplary variant of a display view of an upstream leakdetector. The display has two switched pages: main page 1201 with leakand impulse noise levels and density, and second page 1202 with ahistogram of the distribution leak burst vs duration. The main page isused to show alarming events of detection leak and impulse noise. Thesecond page with the histogram is used for identification MAC address ofCM which generates leak signal.

The main page 1201 includes the row 1203 with icons for indication GPSstatus, wireless signal strength, data transmission events (blinkingarrows) and battery charge status. The next row 1204 indicates thecentral frequency of the upstream channel and bandwidth. The next tworows 1205 and 1206 indicate the field strength of leak with number ofdetected bursts, and the field strength of the impulse noise with thenumber of detected impulses per measuring session accordingly. Note thatthe simultaneous reporting of the results of the detection of leakageand impulse noise to server 105 and indication on display 514, providesan indication of the most probable zones of injection Ingress (impulsenoise) in upstream bandwidth.

There is a hot button, “Histogram” 1207, shown at the bottom of theexemplary main page 1201. After pressing this button, the display willbe switched to second page 1202. The “Back” button 1214 is used toswitch the display back to main page.

The second page 1202 shows a histogram 1208 of the bursts detectedduring a measuring session. There are the following hot buttons at thispage: “All MAC” 1211, “Single MAC” 1212 and “AVG On/Off” 1213.

The algorithm to the identification of the MAC address of the CM whichis the source of leak signal is as follows. After switching to page 1202the detector will be in a default mode “All MAC” in which server 105sends pings to all of the CMs around truck 101 (FIG. 1). Then afterpressing the button “AVG On” on the display, bars will be accumulatedwhich correspond to the duration of the dominant bursts with pingresponse data. Those bars are assigned by dotted line 1215. Note,particular duration of bursts corresponding to the response of a CM onpings, depends on the CMTS settings, so, in common cases, it is not easyto calculate the expected bursts durations without having detailedinformation about the CMTS settings, UCD and etc. The only one practicalway is just to measure dominant bursts durations in each particularcase. After an accumulation of enough data, the dotted line 1215 will bestabilized. At this moment, it makes sense to press the button “SingleMAC”, and detector 114 (FIG. 1) will send a request to server 105 tosend pings to the first MAC address in the list with all MACs. Server105 will send a message back to detector 114 with selected single MACaddress and start to send pings to the above MAC addresses only. Byusing arrow buttons 1210, the technician can select the next MAC in thelist at server 105 until the bars in the display will not matched goodenough with dot line 1215.

Note, in “Single MAC” mode, the technician can also press the “AVG On”button and dotted line 1215 will be saved at display because the resetdotted line 1215 is allowed at “All MAC” mode only. Of course, theprocess of identification MAC address will improve over time as thetechnician gains more experience, but the new method and systemaccording to the Application is still a more effective and lower costmethod compared with using a directional antenna for location leaksource, especially taking into account that at return bandwidthdirectional antenna will have a very big size making using this antennaunpractical for mobile use on a vehicle.

The new identification MAC address process of location leak (e.g. theshielding fault 112 in FIG. 1) will be much easy for a technician thanprevious methods of the prior art. For example, in urban areas, the newMAC address method allows a technician to locate an exact apartmentwhere leak is generated. In countryside areas typical across manycountries, such as the U.S., identification of a specific MAC addressallows for the selection of a drop line and then a near field antennacan be used to find the leak along that particular drop line.

The leakage detector of FIG. 5 according to the Application, can beimplemented as a low-cost unit in a compact form factor. There can alsobe a fully automatic mode which during the vehicle patrol, canautomatically store and/or send historical data to the server 105.Following such automatic measurements, a technician will have a chanceto check the results of detection leak directly in the field and thenidentify MAC address of CM generates leak.

Regarding testing in general by pings, we tested different ways tosimulate upstream traffic at cable distribution sites in an actual HFCnetwork. Various configurations of reading commands were tested,downstream spectrum capture commands, and ping commands with differentrates and payloads (for ping, the size of the test data packet). Theconclusion was that the literal command ping was found to be aparticularly effective and flexible method for the new system andmethods of the Application, because the rate of pings and the payloadcan both be controlled. However, as described hereinabove in thedefinitions, we include in our use of the term ping, any suitablecommand which causes a return of any suitable data packet or data. Thatis, we use the term ping in the broadest sense to includes other ways ofmodem stimulation. Also, we noted that particularly in the U.S.,upstream traffic is possible, especially including scenario when formonitoring leaks during times with statistically maximal US traffic(such as, for example, in the evening, when people are home and likelyto be using the cable modem). In such cases, some upstream leakagemeasurements can be made without the additional ping stimulation oftraffic to cause a simulated upstream traffic from each modem.

Thus, the new method and systems of the Application can also be usedefficiently to locate leakage within the upstream bandwidth of a cablenetwork based on upstream traffic related to customer use of the cablemodem during higher use periods. In such cases a patrol can be madewithout a need to ping individual modems. Also, there is still no needto actually decode any of the data transmissions, where the new methodand system can verify a leak from the cable system and distinguish theburst or impulse from non-cable system related impulse noise by merelydetermining the presence of an ATDMA preamble or an OFDMA cyclic prefixwithout decoding said ATDMA preamble or said OFDMA cyclic prefix.

For example, a method for leakage detection at a return bandwidth of anHFC network without using patrol vehicle generated pings, includes:providing an apparatus for use in a patrol vehicle, the apparatusincluding a GPS receiver and a burst and impulse noise detector, bothcoupled to a processor; recording GPS coordinates of a location of thepatrol vehicle for correlation to known locations of cable modems (CM);listening for leakage bursts from a group of CM sending upstream datawithin a current location of the patrol vehicle; detecting by the burstand impulse noise detector both upstream burst leakage and off-airimpulse noise; measuring a duration of each detected burst leakage andoff-air impulse noise event to classify and separate each detected eventas either a leak burst or a noise impulse; and for a verification ofeach leak burst, detecting a presence of an ATDMA preamble or an OFDMAcyclic prefix without decoding the ATDMA preamble or the OFDMA cyclicprefix.

In summary, a method for leakage detection at a return bandwidth of anHFC network includes: providing an apparatus for use in a patrolvehicle, the apparatus including a GPS receiver and a burst and impulsenoise detector, both coupled to a processor; sending GPS coordinates ofa location of the patrol vehicle to a leakage data server; selecting agroup of cable modems (CM) within a current location of the patrolvehicle; stimulating an upstream traffic by sending pings to the groupof CM; detecting by the burst and impulse noise detector both upstreamburst leakage and off-air impulse noise; measuring a duration of eachdetected burst leakage and off-air impulse noise event to classify andseparate each detected event as either a leak burst or a noise impulse;for a verification of each leak burst, detecting a presence of an ATDMApreamble or an OFDMA cyclic prefix without decoding the ATDMA preambleor the OFDMA cyclic prefix; and for a further verification of each leakburst, matching a time stamp of each leak burst with a minislot or asymbols time grid.

The step of providing can further include providing a wireless modem,and the step of selecting includes selecting the group of CM within thecurrent location of the patrol vehicle by querying a remote server viathe wireless modem.

A method for identification of a MAC address of a cable modem (CM) whichis generating a leak signal includes: providing an apparatus for use ina patrol vehicle, the apparatus including a GPS receiver and a burst andimpulse noise detector, both coupled to a processor; sending GPScoordinates of a location of the patrol vehicle to a leakage dataserver; selecting a group of cable modems (CM) within a current locationof the patrol vehicle; stimulating the group of CM to provide astimulated upstream traffic by sending pings to the group of CM;detecting an average (AVG) dominant duration of bursts during thestimulated upstream traffic from CMs within a zone of a detected leak;and stimulating an upstream traffic from each single MAC address of theCMs within the zone of the detection leak one by one until a matchingdominant duration of bursts measured during the step of simulating anupstream traffic by sending pings to the group of CMs is found toidentify a particular CM associated with an upstream leak.

The method can further include, following the step of stimulating, astep of prioritizing two or more potential ingress events at an upstreambandwidth of a hybrid fiber coax (HFC) system by a comparison ofupstream leak noise and ambient impulse noise.

An upstream leak detection system includes a leak detection apparatusconfigured for use in a mobile patrol vehicle. The leak detectionapparatus includes a processor, a GPS receiver and a burst and impulsenoise detector, both operatively coupled to the processor. A leakagedata server includes a database with cable modems (CMs) physical and IPaddresses and a core to stimulate an upstream traffic from a pluralityof CM in a current vicinity of the mobile patrol vehicle.

The upstream leak detection system can further include a wireless modemoperatively coupled to the processor and where the leakage data serverresides on a remote server communicatively coupled to the upstream leakdetection system by the wireless modem.

The upstream leak detection system can further include a display to showinformation about detected leaks or impulse noise.

The upstream leak detection system can further include a display to showa histogram of a number of bursts in a time interval against bins ofduration of bursts.

The upstream leak detection system can further include a display to showinformation about detected leaks or impulse noise.

The upstream leak detection system can further include a display to showa histogram of a number of bursts in a time interval against bins ofduration of bursts.

The burst and impulse noise detector can include an antenna operativelycoupled to a detection of burst leak signals circuit via at least one ofa filter and an amplifier.

The burst and impulse noise detector can include an antenna operativelycoupled to the detection of burst leak signals circuit via a bandpassfilter (BPF), and low noise amplifier (LNA), and a low pass filter(LPF).

The burst and impulse noise detector can include an antenna operativelycoupled to a detection of burst leak signals circuit via at least one ofthe filter and the amplifier and following the at least one of thefilter and the amplifier, an analog to digital converter, to digitizereceived bursts coupled to the detection of burst leak signals circuit.

The detection of burst leak signals circuit can include an I/Q downconverter coupled to an envelope detector and an autocorrelationdetector. An impulse level meter and a comparator are coupled to theenvelope detector. A burst/impulse noise controller is coupled to thecomparator, the impulse level meter, and the autocorrelation detector.The burst/impulse noise controller is adapted to provide informationabout each impulse or burst for a determination of a duration of theimpulse or burst, an indication if each received impulse or burstincludes a preamble of an ATDMA burst or a cyclic prefix of a OFDMAburst, and a time stamp of the received impulse or burst by thedetection of burst leak signals circuit operating in conjunction withthe processor operatively coupled to the detection of burst leak signalscircuit.

The autocorrelation detector can include a correlation processor whichdetects an ATDMA preamble by a start of correlation based on a risingedge of a pulse indicative of a start of the ATDMA burst, and a fallingedge indicative of and end of the ATDMA burst based on a number ofminislots.

A method for leakage detection at a return bandwidth of an HFC networkincludes: providing an apparatus for use in a patrol vehicle, theapparatus including a GPS receiver and a burst and impulse noisedetector, both coupled to a processor; recording GPS coordinates of alocation of the patrol vehicle for correlation to known locations ofcable modems (CM); listening for leakage bursts from a group of CMsending upstream data within a current location of the patrol vehicle;detecting by the burst and impulse noise detector both upstream burstleakage and off-air impulse noise; measuring a duration of each detectedburst leakage and off-air impulse noise event to classify and separateeach detected event as either a leak burst or a noise impulse; and for averification of each leak burst, detecting a presence of an ATDMApreamble or an OFDMA cyclic prefix without decoding the ATDMA preambleor the OFDMA cyclic prefix.

The autocorrelation detector can include an OFDMA cyclic prefixauto-correlation detector including at time delay line and amultiplier-integrator wherein correlation is based on a time delay of 20μs in a 2 k FFT mode or 40 μs in a 4 k FFT mode during a burststart-stop interval.

Part 2—OUDP Leakage Detection

OUDP (OFDM Upstream Data Profile) is built into some of the variousDOCSIS® specifications. While OUDP was not intended to be used forleakage testing, we realized that combined with some of the new methodsdescribed herein, OUDP can be used for leakage testing.

For OUDP leakage detection, the CMTS (Cable Modem Termination System)directs the CM (cable modem) to transmit an OFDMA signal with certainparameters. In combination with some of the techniques described herein,we realized that the OUDP OFDMA signals can be detected using a matchedfilter approach, such as by using the cyclic prefix of the OFDMA andpilot pattern for leakage detection.

In the context of the Application, ping includes generation by a CM ofany suitable signal into the upstream cable path, including, for examplea probing OFDMA signal or an OUDP burst, such as can be used for OUDPleakage detection.

FIG. 13 is a drawing showing a diagram of an exemplary system formonitoring leakage in aeronautical band of high split HFC for both part2, as well as common to all parts of this Application as a common highlevel block diagram. Detection vehicle 2101 includes a leakage detector2103. Leakage detector 2103 includes a GPS receiver 2104, a leak signalreceiver 2105, and a wireless modem 2106. Detection vehicle 2101 is incommunication via communication line 2116 with leakage data server 2107,and typically via the leakage data server 2107 with the Cable ModemTermination System (CMTS) 2117, and cable modem (CM) database 2108. CMTS2117 is also operatively coupled by CMs control 2118 to CMs of the cablesystem 2109 having CMs 2112, 2113, and 2114, etc. Upstream signal 2115are from the CMs. Exemplary leakage includes leakage at the trunk line2111, and leakage at a drop line 2110.

FIG. 14 is a drawing illustrating the concept permanent generation by CMOUDP bursts for monitoring leakage.

FIG. 15 is a drawing which shows an example of an OUDP burst signal intime-frequency domain for a pilot pattern 11 (a preferable pilot patternfor leak detection due to maximal energy of pilots within the minislot).

FIG. 16 is a drawing which illustrates binary phase shift keying (BPSK)modulation of OUDP pilots according to DOCSIS 3.1 specs.

FIG. 17 is a drawing showing a block diagram of an OUDP burst detectorwith an adaptive matched filter and on-line receiving of coefficients ofa matched filter from the leak data server (e.g. FIG. 13, leakage dataserver 2107). Leakage antenna 2501 is electrically coupled to filterpre-selector 2502. LNA 2503 amplifies signals from the filterpre-selector 2502 for the low IF down-converter 2504. Analog to digitalconverter (ADC) 2505 is coupled to an output of the low IFdown-converter 2504. A matched filter for OUDP burst 2506 is coupled toan output of the ADC 2505. The matched filter for OUDP burst 2506receives coefficients for a current detection profile from memory 2515(e.g. a flash memory). Matched filter for OUDP burst is operativelycoupled 2506 Flash memory 2525 and CPU 2507. The digital sections of thelow IF down-converter 2504, the ADC 2505, and matched filter for OUDPburst 2506 can be coupled to and run on a common clock 2513, such as canbe provided by a GPS time sync module 2508, which GPS time sync module2508 can also provide GPS data to CPU 2507. GPS time sync module 2508receives GPS satellite signals via GPS antenna 2509. Display 2512 canshow both settings of the leakage detector as well as results computedby a processor of CPU 2507. The leakage detector according to FIG. 17can be wirelessly coupled via wireless modem 2510 and antenna 2511, suchas to provide the communications line 2116 of FIG. 13.

FIG. 18 is a flow chart showing an exemplary operation of an OUDP leakdetector according to the Application. The exemplary steps includefollowing start 2601, Connect to leak data server and sending reportwith current GPS coordinates 2602, Receiving from Leak data servercoefficients of OUDP matched filter for current leak detector location(hub, node) 2603, Storing coefficients of OUDP matched filter in flashmemory and re-programming matched filter 2604, start new detectionsession duration one second 2605, Verification: Max level at the outputof matched filter is over detection threshold? 2606, No—Sending reportto leak data server with current time stamp—GPS coordinates anddecision—No leak 2607, Yes—Measuring time stamp and level of all peaksat the output of matched filter which are over detection threshold 2608,Selection of dominant peaks from peaks of side lobes and calculation ofa number of dominant peaks 2609, Calculation leak level (AVG or Max) byusing measured values of dominant peaks at the output of matched filter2610, Indication leak level at display and sending report to leak dataserver with current time stamp, GPS coordinates, leak level and numberof dominant peaks during detection session 2611, loop to 2605,otherwise, Push button “Map” and receiving from server after somemeasuring sessions map picture with flag where leak is located andmessage about leak location in trunk or drop line and CM's MAC address2612.

Note that the method of FIG. 18 can also be performed without a GPSreceiver, or without use of GPS data, where, for example, physicallocations are determined by an identifier of any particular hardwarebox, such as, for example, a MAC address of a CM.

Note that, at steps 2608 and 2609 a procedure of selection dominantpeaks of cross-correlation process function can be added at the outputof matched filter. This process algorithm can define the number of OUDPburst detected during a detection session of, for example, 1 second, andthen makes a decision at the server if a detected leak signal is comingfrom a trunk line (e.g. where there are multiple peaks from many CMs),or from a drop line (e.g. single or two peaks from one CM).

FIG. 19 is a drawing showing a graph which illustrates an exemplaryactual correlation process function at the output of OUDP matched filterfor a pilot pattern 11. An important feature of this process function isthat besides the dominant peak, peak of cross-correlation processfunction 2701, there are many lower level side lobes peaks, side lobesof cross-correlation process function 2702 due to the nature of thepilot pattern. The side lobes peaks can be over the detection thresholdand a selection process can be used for a correct calculation of aproper number of dominant peaks (i.e. the number of CMs).

FIG. 20 is a graph which illustrates the concept of a process algorithmfor the selection of dominant peaks. A detection threshold 2807 providesa starting point for the detection of a max level peak and for definingfrom this peak, time slots where there could be other dominant peaks.The duration of the above time slot is equal to the duration of the OUDPburst signal. Over the exemplary 1 second measuring duration, there aretime slots 2804. A peak 2806 in a first time slot is followed in a thirdtime slot by a peak with max level 2801 in a in a time slot of max levelpeak 2802, with side lobes 2803. In a fifth time slot of the time slotsfor other dominant peaks 2804, is peak 2805. The exemplary detectionthreshold is shown as detection threshold 2807.

FIG. 21A is a drawing showing a flow chart of an exemplary leak dataserver operation after an operator presses the “Map” button (FIG. 21A)at a field unit.

The exemplary steps include: Receiving a request “Map” from field unit(after press button “Map” at filed unit) 2901, Verification: Leak sourceis in drop line (just one or two dominant peaks what means leak signalis generated by single CMs)? 2902, No—Sending to field unit map picturewith flag at leak location and message: “Trunk line” 2903, Yes—Sendingrequest to CMTS (or direct to CMs) to switch off OUDP at half of activeCMs in node around field unit location 2913, Receiving next report fromfiled unit 2904, Verification: Leak signal is detected? 2905, No—Sendingrequest to CMTS (or direct to CMs) to switch on OUDP at half of CMswhich was switched off at previous request and to switch off OUDP at CMswhich was switched on at previous request 2906 and loop to 2904,Yes—Verification: Number of active CMs around filed unit location ismore than one? 2907, Yes—loop to 2913, No—Sending to field unit mappicture with flag at leak location and message: “Drop line, MAC ______”2908, Sending request to CMTS (or direct to CMs) to switch on OUDP atall CMs in the node 2909.

This process algorithm can define if the leak comes from a trunk line ora drop line and the Mac address of the associated CM.

FIG. 21B is a drawing showing exemplary display screens of an exemplaryOUDP detector with “Map” mode with detection MAC address.

OUDP burst duration—As noted at the beginning of Part 2, we realizedthat combined with some of the new methods described herein, OUDP canalso be used for leakage testing. The same previously described conceptsas illustrated by FIG. 5, FIG. 6, FIG. 11, and FIG. 12 are now appliedto OUDP burst duration for leak validation

In combination with some of the techniques described herein, we realizedthat the OUDP and OFDMA signals can be detected using an energy burstdetector. This method is described in Part 1 of the application forATDMA bursts. In this case of OUDP bursts, burst durations are measured,and then the measured burst durations are compared with expected valuesof burst durations. The system and method of detection and validationOUDP burst includes, measuring duration of detected bursts, collectinghistogram of burst durations during measuring session and then comparethe histogram of burst durations with expected durations of OUDP bursts.

Auto-correlation cyclic prefix of OUDP bursts—As noted at the beginningof Part 2, we realized that combined with some of the new methodsdescribed herein, OUDP can be used for leakage testing. The samepreviously described concepts as illustrated by FIG. 9, FIG. 10, andFIG. 11 are now applied to Auto-correlation cyclic prefix of OUDP burstsfor leak validation.

Another system and method of detection OUDP can use an auto-correlationof cyclic prefix of OUDP bursts (OUDP bursts are similar to OFDMAbursts). This method for OUDP bursts is the same as is describedhereinabove in Part 1 of the Application for OFDMA bursts. One systemand method of detection of OUDP bursts includes auto-correlating cyclicprefixes of OFDMA symbols within OUDP bursts, and then accumulatingcoherent responses of the auto-correlation functions from the symbolswithin the OUDP bursts.

Part 3 CW Signals

A challenge now exists with some of the new architectures beingconsidered, specifically high-split systems where the upstream spectrumcovers a frequency bandwidth up to 204 MHz as well as Full Duplexsystems where the downstream and upstream frequency bands overlap in theaeronautical band. For both of these new architectures, transmittedcarriers within the aeronautical band which is mandated by the FCC to bemonitored for signal leakage, are now no longer generated from theheadend or from the node in the forward direction—but are alternativelynow generated from equipment in the customer premises in the form ofcable modems, and are transmitted from the customer premises to theheadend utilizing return path frequencies. As such, the status quotechniques used to monitor for signal leakage are no longer practical touse.

An exemplary embodiment of system for monitoring leakage at aeronauticalband of high split HFC network according to the present application isillustrated in the schematic block diagram of FIG. 22. As an example,this embodiment includes field leakage detector 33114 installed on truck33101 and leakage data server 33107 with database of cable modems (CM)in HFC network. Field leakage detector 33103 includes pilot leakdetector 33105, GPS receiver 33104, and wireless modem 33106.

The system of FIG. 22 works as follows: As was noted above at high splitHFC network 109 aeronautical band 108-137 MHz is covered by upstreambandwidth 5-204 MHz, so, leakage at drop line 33110 and trunk line 33111will be produced from upstream signals 33115 generated by cable modems(CM) 33112, 33113 and 33114. Upstream signal 33115 at high split HFCnetwork in aeronautical band 108-137 MHz is OFDMA burst signal.Monitoring leakage from this signal is a challenge because this is aspread spectrum random signal and for this type of noise signal, it isnot easy to provide good sensitivity and validation of detection.

The next problem of monitoring leakage from OFDMA upstream signal isthat TX sessions of CMs 33112 . . . 33114 are controlled by CMTSaccording on many different criteria. So, there is no way to guaranteethat CMs 33112 . . . 33114 will generate an OFDMA upstream signal inaeronautical band exactly when the truck 33101 with leak detector 33103will be at close proximity to leak sources 33110 and 33111.

To overcome above issues with detection random OFDMA signal according topresent application, each CM 33112 . . . 33114 in the HFC network 33109permanently generates a narrow bandwidth pilot signal for monitoringleakage. The pilot signal is placed into an exclusion bandwidth of theupstream OFDMA spectrum within the aeronautical band 108-137 MHz. Also,each CM within one node has a specific frequency offset of a pilotsignal to prevent cumulative effect of pilots from different CMs intrunk line (at location of leak source 33111). Specifications of thepilot signal generated by CMs 33112 . . . 33114 are described in detailhereinbelow.

Exemplary leakage detector 33103 detects a leak from the pilot signalsgenerated by the CMs 33112 . . . 33114 and, each second send reports33116 via wireless modem 106 to the leakage data server 107. The reportincludes data about the level of detected leaks, exact frequencies ofdetected pilot signals, current GPS coordinates of truck 33101, and GPStime stamps. Leakage data server 33107 analyses the GPS coordinates anddefines an HFC network node where truck 33101 is currently located. Thenserver 33107 analyses the frequencies of the detected pilots andcompares it with CM's settings at database 33108. This analysis allowsserver 33107 to define MAC addresses of CMs from which the pilot signalwas detected. This information is then used by server 33107 to definethe exact location of the leak source by using an electronic map of theHFC network and physical addresses of MACs in database 33108. Forexample, if detected pilots correspond to a single CM or to a few CMswith the same physical address, then the probable leak location is atdrop line (leak source 33110) at the corresponding physical address. Ifdetected pilots correspond to multiple CMs with different physicaladdresses, then the probable location of leak source is in a trunk line(leak 33111 in FIG. 22) at the nearest proximity to physical address ofCM which is more close to CMTS (CM 33112 in FIG. 22).

Note that while a GPS element on the truck can be useful, the GPS is notrequired. For example, in a system without GPS, or not using GPS, aphysical address can be determined directly from a MAC address of theCM.

Also, for example in the context of an OUDP based system, the OUDPformat may vary and/or there may be different OUDP configurations fordifferent geographical areas which would necessitate different OUDPmatched filter coefficients. In such cases, a GPS equipped leakagedetection vehicle can automatically load the correct OUDP settings inany particular GPS location (e.g. for any given hub's profile).

However, where there is only one profile, a vehicle can perform leakagedetection methods of the application either without a GPS or without GPSinformation, where physical locations can be established by knowlocations of identifiable hardware, such as, for example, a knownphysical address/location of a CM as determined by its MAC address orother suitable physical box identifier.

The structure of an exemplary pilot signal generated by a CM is shown inFIG. 23. The pilot signal includes two CW pilot carriers 3101 and 3102.The first CW pilot 3101 in FIG. 23 has central frequency fi (3103). Thisfrequency fi is specific for particular CM “i” in the node and all CMswithin one node has different frequencies fi. All frequencies fi arelocated within bandwidth 3106 with central frequency f₀ 3107. So, eachfrequency fi has specific frequency offset Fi 3108 from frequency f₀.This offset Fi 3108 is installed at CM by CMTS and then stored at CM'sdatabase 33108 (FIG. 22). In other words, each MAC address of CM indatabase 33108 is associated as with physical address of CM and withfrequency offset Fi too. Thus, measuring the frequency offset Fi at theleak detector 33103 allows to recognize MAC address of CM and thendefine physical address of CM from which leak signal was generated. Thisinformation, as was noted above, allows to locate leak source 33110 and33111 in the network 109 (see FIG. 1).

The frequency offset between first CW pilots 3101 and second CW pilot3102 is “Delta F” (3104), so, the second CW pilot is located atfrequency fi+Delta (3105). This frequency offset “Delta F” is generatedin CM very precisely with accuracy less than 1 Hz what allows then atleak detector side to use measured frequency offset for leak validation.It should be noted, that generation of CW pilots is standard operationmode in modern DOCSIS 3.1 CMs because this mode is also used forsounding interfering groups for full duplex.

In the case of a location leak source in drop line (see leak 33110 inFIG. 22) and single CM in the home the leak signal will look as shown inFIG. 23.

However, if the leak source is located in a trunk line (e.g. leak 33111in FIG. 22) the leak signal will be combination of pilots from differentCMs. This combined signal is illustrated in FIG. 24. The first CW pilots3201 from different CMs are located within bandwidth 3203 and the secondCW pilots 3202 are located within bandwidth 3204. The first CW pilots3201 has specific central frequencies 3206 (f1, f2, f3, . . . fi, . . .fn), but the frequency offset “Delta F” 3205 between the first andsecond CW pilots is the same for different CMs. Thus, fixed frequencyoffset “Delta F” at each CM allows to validate leak signal even in caseof combining pilot signal in trunk line. From the other side usingspecific frequency offset Fi (FIG. 23) allows to split CW pilots 3201and 3202 in the case of a location leak at trunk line and combiningpilots from different CMs. For good separation CW pilots 3201 and 3202in leak detector the minimal offset between adjacent CWs must be atleast in ten times more than frequency resolution of the leak detector.Most modern leak detectors use an FFT spectrum analyzer for detection ofCW pilots. The potential frequency resolution of FFT spectrum analyzerfirst of all depends on measuring time. However, measuring time duringpatrolling leak on truck is limited one or even half of second. It meansthat potential frequency resolution in case of measuring time equals tohalf second will be around few Hz. Thus, the reasonable minimal step offrequency offset Fi (FIG. 23, 24) should be around tens Hz, for example,30 . . . 50 Hz.

The bandwidths 3203 and 3204 used for the first and the second CW pilotsdepends on the maximal number of CMs in the node. For example, in thecase of 250 CMs in a node (more than the typical value) the bandwidth3203 and 3204 used can be calculated as 50 Hz×250=12.5 kHz.

The total bandwidth 3207 for placing all first 3201 and second 3202 CWpilots depends from frequency offset “Delta F”. Offset “Delta F” 3205should be more than bandwidth 3203 to prevent overlapping bandwidths3203 and 3204. An example is to select guard interval between bandwidths3203 and 3204 as 12.5 kHz where the frequency offset “Delta F” will be25 kHz and the total bandwidth 3207 will be 37.5 kHz.

In FIG. 25 is shown example of placing pilot signal in FIG. 24 into anexclusion bandwidth of upstream OFDMA spectrum for scenario 4 k FFTmode. In this case OFDMA subcarrier spacing is 25 kHz (3304). The totalbandwidth 37.5 kHz (3305) of pilot signal is placed into exclusionbandwidth 75 kHz (3303). This exclusion bandwidth 3303 includes 3excluded subcarriers and located between active subcarriers 3301, 3302and within aeronautical band 108-137 MHz. The frequency bandwidth 3307and 3308 for first and second CW pilots are located symmetrical fromboth sides of central (second) excluded subcarrier to preventinterfering with active subcarriers 3301 and 3302 at CMTS Rx side.Additionally, for preventing interfering the level of CW pilots isinstalled at CMs on 10 . . . 15 dBc below (3309) of active OFDMAsubcarriers 3301 and 3302.

FIG. 26 is a drawing showing a block diagram of an exemplary leakagedetector 33103 (FIG. 22) suitable to perform the new methods of part 3of the Application.

A method of monitoring leakage of a high-split HFC network in anaeronautical band includes: generation by cable modems (CM) pilot signalwithin an upstream OFDMA excluded bandwidth; patrolling near or inpre-defined geographic area with a leak detector including: pilot signaldetector; GPS receiver and wireless modem; sending online report fromleak detector to leak data server with CM database, said CM databasecomprising a location of each CM in said pre-defined geographic area,electronic map of HFC networks and parameters of pilot signals; andlocation physical address of leak source by analysis at leak data serverparameters of detected pilot signals from CMs and correlation it withCM's data base.

The pilot signal generated by CM can be a pair of two CW signals withfixed and predefined frequency offset between CW signals.

The first CW signal can have a specific frequency offset of centralfrequency at each particular CM within HFC network node.

The leak detector can be an FFT spectrum analyzer provided frequencyresolution of pilot signals from different CMs and measuring frequencyoffsets of central frequency of first CW pilot and frequency offsetbetween first and second CW signals.

The validation leak signal in leak detector can be provided bycorrelation measured frequency offset between first and second CW pilotswith predefined frequency offset

The report from leak detector to leak data server can include a timestamp, GPS coordinates, detected pilot signal level and frequencyoffsets of first CW signal for each detected pilot signal.

The pilot signal generated by CM can be a pair of two CW signals withfixed and predefined frequency offset.

The CM database can include a location of each CM in said pre-definedgeographic area, electronic map of HFC networks and predefinedparameters of pilot signal at each CM;

The location of leak source at can be provided at leak data server bycorrelation parameters of detected pilot signals with parameters of CMsin database and physical address of CM which is closer to CMTS and whichpilot signal is detected is defined as probable location of leak source.

A method of monitoring leakage of a high-split HFC network in anaeronautical band includes: causing two or more cable modems (CM) in apre-defined geographic area to broadcast pilot signals at differentfrequencies within an OFDMA exclusion zone; patrolling near or in saidpre-defined geographic area with a leak detector, a GPS receiver, and aCM database or a wireless link to a server comprising said CM database,said CM database comprising a location of each CM in said pre-definedgeographic area; and on receiving at least one of said broadcast pilotsignals, correlating a current GPS location with CMs transmitting atsaid different frequencies.

Receiving at least one of said broadcast pilot signals can correspond toa leak from an individual cable drop. Receiving a plurality of saidbroadcast pilot signals can correspond to a leak from a trunk line.

Part 4 CW Signals FDMA

FIG. 27 and FIG. 28 show an exemplary CW-TDMA mode. The CW-TDMA mode canbe viewed as a combination of the OUDP-TDMA and CW modes. The leakagedetector of FIG. 26 can be used to perform leakage detection in theCW-TDMA mode. FIG. 27 is a drawing showing a graph of time versusfrequency for exemplary OFDMA bursts at F1 and F2. FIG. 28 is a drawingshowing exemplary CW test signal in the exclusion bandwidth adjacent toactive OFDMA subcarriers.

Software and/or firmware for the new system and method of leakagedetection within the upstream bandwidth of the HFC network describedhereinabove can be provided on a computer readable non-transitorystorage medium. A computer readable non-transitory storage medium asnon-transitory data storage includes any data stored on any suitablemedia in a non-fleeting manner. Such data storage includes any suitablecomputer readable non-transitory storage medium, including, but notlimited to hard drives, non-volatile RAM, SSD devices, CDs, DVDs, etc.

While an embodiment of the new system and method of leakage detectionwithin the upstream bandwidth of the HFC network has been described bythe application, as an exemplary practical implementation for low cost,the present invention is not so limited and other embodiments are alsopossible. It will be appreciated that variants of the above-disclosedand other features and functions, or alternatives thereof, may becombined into many other different systems or applications, such as, forexample, any cable network having an upstream data component where theupstream data from an end user (e.g. from a CM) includes an identifiablepreamble or cyclic prefix. Various presently unforeseen or unanticipatedalternatives, modifications, variations, or improvements therein may besubsequently made by those skilled in the art which are also intended tobe encompassed by the following claims.

What is claimed is:
 1. A method for monitoring leakage in anaeronautical band of a high split HFC by a detection and validation ofOUDP bursts comprising: providing an apparatus for use in a patrolvehicle, the apparatus including a leak signal receiver coupled to aprocessor; measuring a duration of detected bursts to provide aplurality of burst durations; collecting a histogram of said burstdurations during a measuring session to provide a duration histogram;and determining a presence of a leak based on a comparison of saidduration histogram with expected durations of OUDP bursts.
 2. The methodof claim 1, wherein after said step of providing and before said step ofdetermining, further including the steps of: sending GPS coordinates ofa location of the patrol vehicle to a leakage data server; and receivinga plurality of expected durations of OUDP bursts for a current locationof the patrol vehicle.
 3. The method of claim 2, wherein if saidcomparison of said duration histogram with said expected durations ofOUDP bursts exceeds a threshold, sending a report to said leakage dataserver including a time stamp, a GPS coordinate, and a leak level. 4.The method of claim 3, wherein a display is operatively coupled to saidprocessor and after said step of comparing, a step of determining thepresence of the leak includes showing an indication of a detected leakon a map in a vicinity of said current location of the patrol vehicle.5. An upstream leak detection system for monitoring leakage in anaeronautical band of a high split HFC by a detection and validation OUDPbursts comprising: a leak detection apparatus configured for use in amobile patrol vehicle, said leak detection apparatus comprising: aprocessor, a leakage receiver comprising a burst leak signal detector tomeasure a duration of detected bursts, said leakage receiver operativelycoupled to said processor; and a leakage data server including adatabase with cable modems (CMs) physical and IP addresses and a core tostimulate an upstream traffic from a plurality of CM in a currentvicinity of the mobile patrol vehicle.
 6. A method for monitoringleakage in an aeronautical band of a high split HFC by a detection andvalidation OUDP bursts comprising: providing an apparatus for use in apatrol vehicle, the apparatus including a leak signal receiver coupledto a processor; auto-correlating cyclic prefixes of OFDMA symbols withinOUDP bursts by one or more autocorrelation functions to provide aplurality of coherent responses; and determining a presence of a leakbased on an accumulation of said plurality of coherent responses.
 7. Themethod of claim 6, wherein after said step of providing and before saidstep of determining, further including the steps of: sending GPScoordinates of a location of the patrol vehicle to a leakage dataserver; and receiving a plurality of expected coherent responses for acurrent location of the patrol vehicle.
 8. The method of claim 7,wherein if said step of determining said presence of a leak based onsaid accumulation of said plurality of coherent responses exceeds athreshold, sending a report to said leakage data server including a timestamp, a GPS coordinate, and a leak level.
 9. The method of claim 8,wherein a display is operatively coupled to said processor and said stepof determining said presence of said leak, includes showing anindication of a detected leak on a map in a vicinity of said currentlocation of the patrol vehicle.
 10. An upstream leak detection systemfor monitoring leakage in an aeronautical band of a high split HFC by adetection and validation OUDP bursts comprising: a leak detectionapparatus configured for use in a mobile patrol vehicle, said leakdetection apparatus comprising: a processor, a leakage receivercomprising a burst leak signal detector including a process toauto-correlate cyclic prefixes of OFDMA symbols within OUDP bursts byone or more autocorrelation functions to provide a plurality of coherentresponses, said leakage receiver operatively coupled to said processor;and a leakage data server including a database with cable modems (CMs)physical and IP addresses and a core to stimulate an upstream trafficfrom a plurality of CM in a current vicinity of the mobile patrolvehicle.